Digital image processing
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Machine Learning
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Automatic Segmentation of the Papilla in a Fundus Image Based on the C-V Model and a Shape Restraint
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Segmenting Biological Particles in Multispectral Microscopy Images
WACV '07 Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision
MOSAIC: a proximity graph approach for agglomerative clustering
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
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This paper presents a multispectral microscopy system for differential cytology. While conventional practices rely on the analysis of grey scale or RGB color images, presented system uses thirty one spectral bands for analysis. Algorithms designed to enable image segmentation, feature extraction, and classification are presented. Results are presented for the problem of discriminating among four cell types. In addition, classification performance is compared to the case where multispectral information is not taken into consideration. Results show that the developed system and the use of multispectral information along with morphometric information extracted from spectral images can significantly improve the classification performance and aid in the process of cell differentiation.